Subsurface Transport Simulator Research Articles

Transport of Fecal Indicators from Beach Sand to the Surf Zone by Recirculating Seawater: Laboratory Experiments and Numerical Modeling.

Recirculating seawater is an important component of submarine groundwater discharge, yet its role in transporting microbial contaminants from beach sand to coastal water is unknown. This study investigated the extent to which recirculating seawater carries fecal indicators, Enterococcus and bird-associated Catellicoccus, through the beach subsurface. Laboratory experiments and numerical modeling were performed to characterize the transport of fecal indicators suspended in seawater through medium-grained beach sand under transient and saturated flow conditions. Enterococcus was measured both by culture (cENT) and DNA assay (tENT), and Catellicoccus (CAT) by DNA assay. There were differences between transport of tENT and CAT compared to cENT through laboratory columns containing beach sands. Under transient flow conditions, first-order attachment rate coefficients (katt) of DNA markers were greater (∼10 h-1) than katt of cENT (∼1 h-1), although under saturated conditions katt values were similar (∼1 h-1). First-order detachment rate coefficients, kdet, of DNA markers were greater (∼1 h-1) than kdet of cENT (∼0.1h-1) under both types of flow conditions. Incorporating the rate coefficients into field-scale subsurface transport simulations showed that, in this sand type, the contribution of recirculating seawater to surf zone contamination is likely to be minimal unless bird feces are deposited close to the land-sea interface.

Uncertainty quantification for the reliability of the analytical analysis for the simplified model of CO2 geological sequestration

AbstractA hydromechanical model with analytical solutions including pressure evolution and geomechanical deformation for geological CO2 injection and sequestration were introduced in our previous work. However, the reliability and accuracy of the hydromechanical model and the companion analytical solution are uncertain because of the assumptions and simplifications in the analytical model, though it was validated by a few example cases. This study introduces a method to efficiently measure the accuracy of the analytical model and specify the range of acceptable input parameters that can guarantee the accuracy and reliability of the analytical solution. A coupled hydro‐geomechanical subsurface transport simulator, Subsurface Transport over Multiple Phases (STOMP), was adopted as a reference to justify the reliability of the hydromechanical model and the analytical solution. A quasi‐Monte Carlo sampling method was applied to efficiently sample the input parameter space.

Uncertainty quantification for evaluating impacts of caprock and reservoir properties on pressure buildup and ground surface displacement during geological CO2sequestration

A series of numerical test cases refl ecting broad and realistic ranges of geological formation properties was developed to systematically evaluate and compare the impacts of those properties on pressure build-up and ground surface displacement and therefore risks of induced seismicity during CO2 injection. A coupled hydro-geomechanical subsurface transport simulator, STOMP (Subsurface Transport over Multiple Phases), was adopted to simulate the migration of injected CO2 and geome- chanical behaviors of the surrounding geological formations. A quasi-Monte Carlo sampling method was applied to effi ciently sample a high-dimensional parameter space consisting of injection rate and 12 other parameters describing hydrogeological properties of subsurface formations, including poros- ity, permeability, entry pressure, pore-size index, Young's modulus, and Poisson's ratio for both reser- voir and caprock. Generalized cross-validation and analysis of variance methods were used to quanti- tatively measure the signifi cance of the 13 input parameters. For the investigated two-dimensional cases, reservoir porosity, permeability, and injection rate were found to be among the most signifi cant factors affecting the geomechanical responses to the CO2 injection, such as injection pressure and ground surface uplift. We used a quadrature generalized linear model to build a reduced-order model that can estimate the geomechanical response instantly instead of running computationally expensive numerical simulations. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd

Optimal Operation of Soil Aquifer Treatment Systems Considering Parameter Uncertainty

This paper presents a new methodology for determining optimal operation of soil aquifer treatment (SAT) systems considering parameter uncertainty. The problem of optimal operation of SAT systems is formulated and solved in a discrete-time optimal control framework by interfacing the SALQR (Successive Approximation Linear Quadratic Regulator) optimizer with the MSTS (Multiphase Subsurface Transport Simulator) model. Both deterministic and stochastic programming formulations have been solved. Through the use of first-order analysis of uncertainties, the uncertainty of the water content due to the uncertainties of the simulation parameters are evaluated. A chance constrained formulation of the optimization is utilized to account for the uncertainties of water content in the SAT operation. This approach enables one to quantify the uncertainty of the parameter estimates, and automatically account for the parameter uncertainty in the decision-making process through the SAT management model.

Diffusion processes in composite porous media and their numerical integration by random walks: Generalized stochastic differential equations with discontinuous coefficients

Discontinuities in effective subsurface transport properties commonly arise (l) at abrupt contacts between geologic materials (i.e., in composite porous media) and (2) in discrete velocity fields of numerical groundwater‐flow solutions. However, standard random‐walk methods for simulating transport and the theory on which they are based (diffusion theory and the theory of stochastic differential equations (SDEs)) only apply when effective transport properties are sufficiently smooth. Limitations of standard theory have precluded development of random‐walk methods (diffusion processes) that obey advection dispersion equations in composite porous media. In this paper we (1) generalize SDEs to the case of discontinuous coefficients (i.e., step functions) and (2) develop random‐walk methods to numerically integrate these equations. The new random‐walk methods obey advection‐dispersion equations, even in composite media. The techniques retain many of the computational advantages of standard random‐walk methods, including the ability to efficiently simulate solute‐mass distributions and arrival times while suppressing errors such as numerical dispersion. Examples relevant to the simulation of subsurface transport demonstrate the new theory and methods. The results apply to problems found in many scientific disciplines and offer a unique contribution to diffusion theory and the theory of SDEs.

On uncertainty in remediation analysis: variance propagation from subsurface transport to exposure modeling

Addressing long-term potential human exposures to, and health risks from contaminants in the subsurface environment requires the use of models. Because these models must project contaminant behavior into the future, and make use of highly variable landscape properties, there is uncertainty associated with predictions of long-term exposure. Many parameters used in both subsurface contaminant transport simulation and health risk assessment have variance owing to uncertainty and/or variability. These parameters are best represented by ranges or probability distributions rather than single values. Based on a case study with information from an actual site contaminated with trichloroethylene (TCE), we demonstrate the propagation of variance in the simulation of risk using a complex subsurface contaminant transport simulation model integrated with a multi-pathway human health risk model. Ranges of subsurface contaminant concentrations are calculated with the subsurface transport simulator T2VOC (using the associated code ITOUGH2 for uncertainty analysis) for a three-dimensional system in which TCE migrates in both the vadose and saturated zones over extended distances and time scales. The subsurface TCE concentration distributions are passed to CalTOX, a multimedia, multi-pathway exposure model, which is used to calculate risk through multiple exposure pathways based on inhalation, ingestion and dermal contact. Monte Carlo and linear methods are used for the propagation of uncertainty owing to parameter variance. We demonstrate how rank correlation can be used to evaluate contributions to overall uncertainty from each model system. In this sample TCE case study, we find that although exposure model uncertainties are significant, subsurface transport uncertainties are dominant.

Large‐Scale Dispersion in a Sandy Aquifer: Simulation of Subsurface Transport of Environmental Tritium

Large‐scale dispersion in a sandy unconfined aquifer in Denmark was studied by simulating subsurface transport of environmental tritium. Subsurface transport included transport in a moderately deep unsaturated zone and in a relatively long cross section of the aquifer. The tritium data from the site enabled a four‐step modeling analysis comprising (1) estimation of tritium content in the infiltration water, (2) transport in the unsaturated zone, (3) estimation of flux‐averaged tritium concentration in the recharge water, and (4) transport in the groundwater zone. The groundwater model simulations were sensitive to the longitudinal and transverse dispersivity parameters, αL and αr, as a set of parameters, but a model sensitivity analysis showed that it was not possible to identify a unique set of parameter values. A likely range of variation for the two parameters could be identified: (αL, αT); ∈ [(1 m, 0.005 m); (10 m, 0.0 m)] the two parameters being interdependent in that an increase in αL results in a decrease in αT and vice versa. The reported dispersivities represent a scale of 1000 m, the approximate travel distance from the water table to the observation wells. If the estimated αL can be regarded as being of intermediate reliability following earlier defined criteria, the range or the representative set of values then represent the largest scale of earlier reported values. Including our range of αL in the set of reported dispersivities suggests that αL does not increase indefinitely with scale.